Abstract

We present an open-source toolbox, named MMRotate, which provides a coherent algorithm framework of training, inferring, and evaluation for the popular rotated object detection algorithm based on deep learning. MMRotate implements 18 state-of-the-art algorithms and supports the three most frequently used angle definition methods. To facilitate future research and industrial applications of rotated object detection-related problems, we also provide a large number of trained models and detailed benchmarks to give insights into the performance of rotated object detection. MMRotate is publicly released at https://github.com/open-mmlab/mmrotate.

Citation impact

358
total citations
FWCI
19.71
Percentile
100%
References
55
Citations per year

Authors

12

Topics & keywords

Keywords
  • Toolbox
  • Computer science
  • Object detection
  • Artificial intelligence
  • Object (grammar)
  • Open source
  • Computer vision
  • Machine learning
UN Sustainable Development Goals
  • Industry, innovation and infrastructure
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Funding